1. Field of the Invention
The present invention relates to a method of updating coefficients in a channel equalizer and a coefficient updating circuit, and more particularly, to a method of updating coefficients in a channel equalizer using either the Kalman algorithm or the least mean square (LMS) algorithm, and a circuit that may be used to perform the method.
2. Description of the Related Art
Channel equalization is a technique of processing a signal, such as a signal used in digital communication systems, to improve the performance by reducing channel noise, channel distortion, multi-path interference and multi-user interference. Channel equalizers are used mainly in household appliances such as digital TVs and personal communication systems in order to increase the ratio of an input signal relative to interference and thereby reduce the symbol error rate of the input signal.
Advanced Television Systems Committee (ATSC) provides standards for digital high-definition television (HD TV). ATSC document A53B of Aug. 7, 2001, describes approved standards for digital TV and ATSC document A54, Oct. 4, 1995, provides guidelines for the use of these standards. The standards specify specific training sequences that may be incorporated into video signals transmitted by terrestrial broadcast, cable or satellite channel. ATSC document A54 also discloses a method for adapting the filtering response of an equalizer to adequately compensate for channel distortion. This method does not, however, fully account for the higher probability that coefficients for the equalizer are not set at levels sufficient to adequately compensate for channel distortion when the equalizer first operates.
In order to force the convergence of the equalizer's coefficients, a training sequence may be transmitted to and processed by the adaptive equalizer to generate an output signal. This output signal may then be compared with a locally generated or stored version of the expected output signal to generate an error signal. The equalizer coefficients are then adjusted to minimize the value of the error signal, thereby improving the ability of the equalizer to filter an input signal.
A linear filter is typically used for equalizing a channel, but a feedback-type non-linear filter may also be used to remove impulse noise and non-linear distortion occurring in a communication channel and further improve the performance of the equalizer.
The conventional least mean square (LMS) algorithm, which is both relatively simple to implement and requires a relatively small amount of calculation, may be used as an algorithm for updating a tap coefficient of the equalizer. However, although the coefficients may be calculated with a small amount of calculation when using the LMS algorithm, the convergence of the coefficients is relatively slow. Thus, the LMS algorithm is generally unsuitable for a multi-path communication environment in which the speed of and a delay in transmission of data increase.
The Kalman algorithm is a representative algorithm having relatively fast convergence characteristics. The Kalman algorithm however, presents application difficulties because it requires a large amount of calculation. Although advances in hardware have enabled the wider use of the Kalman algorithm, the large amount of calculation and divergence of coefficients remain problematic for applications of the Kalman algorithm.